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the reference number 27697, via our online portal: Apply now via https://jobs.uksh.de/job/Kiel-PhD-%28mfd%29-Statistical-Genetics-Machine-Learning-Schl-24105/1279933701/ For more information visit: www.uksh.de
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University of California, San Francisco | San Francisco, California | United States | about 1 month ago
. Basic knowledge of statistics and machine-learning Basic programming skills in R and/or Python Basic knowledge of mixed effects models Preferred Qualifications Master's degree in Data Science (or related
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. ESSENTIAL REQUIREMENTS A PhD inMachine Learning, Computer Vision, Computer Science, Physics, Engineering, Mathematics or related areas. Documented expertise in: Machine/Deep Learning, and possibly Computer
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technologies such as IoT, big data, analytics, computer vision, cloud computing, and artificial intelligence (AI). IoT devices help in data collection. Sensors plugged in tractors and trucks as well as in fields
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, computer scientists, and technology innovators. Located in the heart of Las Vegas, the College serves a diverse student population and offers strong academic programs in electrical and computer engineering
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equations, stochastic partial differential equations, stochastic mean-field equations, stochastic control and filtering, stochastics for data analysis and machine learning. These areas will be prioritized
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surface-chemistry trends across selected metals and their oxides. These data will support the construction of a machine-learning force field tailored to NHC–surface systems, enabling large-scale molecular
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California State University, Long Beach | Long Beach, California | United States | about 19 hours ago
subfield involving large data that may require the use of tools such as machine learning or artificial intelligence or computationally intensive simulations Potential for attracting external funding
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Stanford University is seeking a Research Data Analyst 2 to manage and analyze large amounts of information, typically technical or scientific in nature, independently with minimal supervision. Stanford's
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Mathematics (Inverse Problems), Computer Science (Machine Learning, Computer Vision, Efficient Algorithms and High-Performance Computing), and Physics (Image Formation Modelling). Your project is part of